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A Distributed Coordination Framework for Wireless Sensor and Actor Networks

This paper discusses a distributed coordination framework for Wireless Sensor and Actor Networks (WSANs) to establish efficient data paths and meet real-time and energy requirements.

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A Distributed Coordination Framework for Wireless Sensor and Actor Networks

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  1. ADistributedCoordinationFrameworkforWirelessSensorandActorNetworksADistributedCoordinationFrameworkforWirelessSensorandActorNetworks TommasoMelodia,DarioPompili,VehbiC.Gungor,IanF.Akyildiz (MobiHoc2005) PresentedbyTaeheeKim . Thisisbasedonapresentationfileof‘TommasoMelodia’atMobihoc2005.

  2. WirelessSensorandActorNetworks(WSANs) • Sensors • Passiveelementssensingtheenvironment • Limitedenergy,processing,andcommunicationcapabilities • Actors • Activeelementsactingontheenvironment • Higherprocessingandcommunicationcapabilities • Lessconstrainedenergyresources(longerbatterylifeorconstantpowersource) 1/26

  3. WSANApplication • DistributedRobotics&SensorNetwork: • (Mobile)robotsdispersedthroughoutasensornetwork • EnvironmentalApplications: • Detectingandextinguishingforesestfire • BattlefieldApplications: • Sensorsdetectminesorexplosivesubstances • Actorsannihilatethemorfunctionastanks • Microclimatecontrolinbuildings: • Incaseofveryhighorlowtemperaturevalues,triggertheaudioalarmactorsinthatarea 2/26

  4. WSANsvs.WirelessSensorNetworks • Real-TimeRequirementsforTimelyActions • Rapidlyrespondtosensorinput • Toperformrightactions,sensordatamustbevalidatthetimeofacting • HeterogeneousNodeDeployment • SensorDenselydeployed • ActorLooselydeployed • CoordinationRequirements • Sensor-ActorCoordination • Actor-ActorCoordination 3/26

  5. WSANCommunicationArchitecture SensorsActors • Nointerventionfromthesinkisnecessary • Localizedinformationexchange • Lowlatency • Distributedsensor-actorandactor-actorcoordinationrequired 4/26

  6. WSANsvs.WirelessSensorNetworks • Needforadistributedcoordinationmechanism: • Sensor-ActorCoordination • Establishdatapathsbetweensensorsandactors • Meetenergyefficiencyandreal-timerequirements • Actor-ActorCoordination • Decision:doesanactionneedtobeperformed? • Whatistheoptimalstrategyfortheactorstodividetheworkload? 5/26

  7. Sensor-ActorCoordination

  8. Sensor-ActorCoordination • Objectives: • Establishdatapathsbetweensensorsandactors • Meetenergyefficiencyandreal-timerequirements • Question: • Towhichactordoeseachsensorsenditsdata? • Whatistheoptimaltreefromsensorstoactors? • OurSolution: EventDrivenClusteringwithMultipleActors 6/26

  9. Reliability(1/2) • Definition1. TheLATENCYBOUNDBisthemaximumallowedtimebetweensamplingofthephysicalfeaturesoftheeventandtheinstantwhentheactorreceivesadatapacketdescribingtheseeventfeatures • Definition2. AdatapacketisEXPIRED(UNRELIABLE),ifitdoesnotmeetthelatencyboundB • Definition3. AdatapacketisUNEXPIRED(RELIABLE),ififisreceivedwithinthelatencyboundB 7/26

  10. Reliability(2/2) • Definition4. TheEVENTRELIABILITYristheratioofreliabledatapacketsoverallpacketsreceivedinadecisioninterval • Definition5. TheEVENTRELIABLITYTHRESHOLDrthistheminimumeventreliabilityrequiredbytheapplication • OBJECTIVE: Complywiththeeventreliabilitythreshold(r>rth)withminimumenergyexpenditure! 8/26

  11. Event-DrivenClusteringwithMultipleActors • Objective: • Findtheoptimalstrategyforevent-drivenclustering (Towhichactorsisdatasent?Whichpathsareused?) • SolutionApproach: • Optimalsolutionobtainedbymeansofmathematicalprogramming • IntegerLinearProgrammingformulation • NP-Complete • NotScalable(<100nodes),centralizedsolution 9/26

  12. DistributedProtocol(1/3) • Objectivesofthedistributedprotocol: • Establishsensor-actordatapaths • Clusterthesensorsintheeventarea • Findtheoptimalworkingpointofthenetwork • r> rth(reliabilityoverthethreshold) • Minimumenergyconsumption • BasedonGeographicalRouting • Decisionstakenbasedoffeedbacksfromactors • Actorcalculatedreliabilityrandbroadcastsitsvaluetothesensors • Sensorsswitchamongstart-up,speed-up,aggregationstate 10/26

  13. DistributedProtocol(2/3) • Sensorsprobabilisticallyswitchamongthreedifferentstatesaccordingtofeedbackfromtheactors: • Start-upState: • Whentheeventoccurs,allsensorsswitchinthestart-upstateandestablishdatapathstotheactorsaccordingtotwo-hoprule • Quicklyestablishadatapathfromeachsourcetooneactor • Compromisebetweenenergyconsumptionandlatency • Actorcalculatedreliabilityrandbroadcastsitsvaluetothesensors • Speed-upState:(Ifr<rth) • Reducethenumberofhopsofsensor-actorpathssoastoreducetheend-to-enddelay(lowerdelay,higherenergyconsumption) • Obtainedbysendingpacketsto“far”neighbors(closertothedestinationactor) 12/26

  14. DistributedProtocol(3/3) • AggregationState:(Ifr<rth) • Reducetheoverallenergyconsumptionwhencompliantwitheventreliability(lowerenergyconsumption,higherdelay) • Sendpacketstocloserneighbors(highernumberofhops) • Theprobabilityofchangingstatemydependonthelack/excessofreliability 13/26

  15. Example:pathestablishment Nodesestablishpathsaccordingto thetwo-hoprule(start-upstate) Eventoccurs! Idlestate Start-upstate 14/26

  16. Example:lowreliability Somesensorsswitchtothespeed-up stateandselectasnexthoptheclosestnodetotheactor->reducelatency Theactoradvertiseslowreliability (r<rth) idlestate start-upstate speed-upstate 15/26

  17. Example:highreliability Somesensorsswitchtotheaggregation stateandselectasnexthoptheclosestnodealreadyinthenode->reduceenergyconsumption Theactoradvertiseshighreliability (r>rth) idlestate start-upstate speed-upstate aggregationstate 16/26

  18. Actor-ActorCoordination

  19. Actor-ActorCoordination • Objective: • Selectthebestactor(s)intermsofactioncompletiontimeandenergyconsumptiontoperformtheaction • Challenges: • Whichactor(s)shouldexecutewhichaction(s)? • Howshouldthemulti-actortaskallocationbedone? 17/26

  20. Actor-ActorCoordinationModel • Definitions: • OverlappingArea • Anareathatcanbeacteduponbymultipleactors • Non-OverlappingArea • Anareathatcanbeacteduponbyonlyoneactor • ActionCompletionTimeBound • Themaximumallowedtimefromtheinstantwhentheeventissensedtotheinstantwhentheactioniscompleted • PowerLevels • Discretelevelsofpowertoperformtheaction.Ahigherpowerlevelcorrespondstoaloweractioncompletiontime 18/26

  21. Actor-ActorCoordinationProblem • ForanOverlappingArea,actor-actorcoordinationproblem: • Selectingasubsetofactors • Adjustingactionpowerlevels • Maximizetheresidualenergyandcompletetheactionwithintheactioncompletionbound • ForaNon-OverlappingArea,actor-actorcoordinationproblem: • Adjustactionpowerlevels • Maximizetheresidualenergy 19/26

  22. Actor-ActorCoordination • OptimalSolution: • Actor-actorcoordinationproblemformulatedasaResidualEnergyMaximizationProblemusingMixedInterNon-LinearProgramming(MINLP) • NP-CompleteProblem • DistributedSolution: • Real-TimeLocalizedAuction-BasedMechanism • Definitions • Seller:Actorreceivingtheeventfeatures • Auctioneer:Actorinchargeofconductingtheauction • Buyer:Actorabletoactonaparticularoverlappingarea /26

  23. Real-TimeLocalizedAuction-BasedMechanism • FortheOverlappingareas: • TheSellerselectsoneauctioneerforeachoverlappingarea,i.e., theclosestactortothecenteroftheoverlappingarea->Energyspentforauctionandauctiontimereduced! • TheSellerinformseachauctioneeroftheauctionareaandoftheactiontimebound • TheAuctioneerdeterminesthewinnersoftheauctionbasedonthebidsreceivedfromthebuyers.Thebidsconsistsofavailableenergy,powerlevelandactioncompletiontime • TheAuctioneerfindsthewinnersbycalculatingtheoptimalsolutionoftheResidualEnergyMaximizationProblem • FortheNon-Overlappingareas: • Theactorisdirectlyassignedtheactiontask 20/26

  24. PerformanceResult

  25. Sensor-ActorCoordination–Energy(1/2) 21/26

  26. Sensor-ActorCoordination–Energy(2/2) 22/26

  27. Sensor-ActorCoordination:Delays 23/26

  28. Sensor-ActorCoordination:PathLength 24/26

  29. Actor-ActorCoordination 25/26

  30. ConclusionsandFutureWork • FirstpapertodealwithintegratednetworksofSensorsandActors • UnifiedframeworkforcommunicationandcoordinationproblemsinWSANs • SolutionsforSensor-ActorcoordinationandActor-Actorcoordination • Focusonreal-timeandenergyconsumption • Futureworkwillincorporatemobilityofactorsandtuningofthenetworkdynamics 26/26

  31. EvolutionofStatesforaSensor

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